Senior Data Engineer- Data Streaming

Company:
Location: Los Angeles, CA 90069

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Pluto TV, a ViacomCBS company, is the leading free streaming television service in America, delivering 250+ live and original channels and thousands of on-demand movies in partnership with major TV networks, movie studios, publishers, and digital media companies. Pluto TV is available on all mobile, web and connected TV streaming devices and millions of viewers tune in each month to watch premium news, TV shows, movies, sports, lifestyle, and trending digital series. Headquartered in West Hollywood, Pluto TV has offices in New York, Silicon Valley, Chicago and Berlin.

Overview & Responsibilities:
The Sr. Data Engineer for streaming will be responsible for supporting and enhancing our Kafka and Kinesis based streaming data collection platforms. The ideal candidate will have strong experience with Kafka (open-source or Confluent) and AWS Kinesis, as well as cloud platforms. The candidate should also be strong with AWS and Kafka components (Topics, Producer/Consumer, KStream, KTable, and KSQL), Kinesis components including streams, firehose and data analytics, and be experienced working with streaming systems that handle very high volume and velocity data. This will require a strong understanding of streaming architectures, and experience with AWS, CI/CD tools, and infrastructure as code. Working as part of the Data Engineering team responsible for managing data feeds and collecting analytical streaming data from our client software. In this fast-paced environment, you will deal with high volume and high velocity data, and demonstrate your strong analytical, problem solving, organizational, and prioritization skills.

B asic Qualifications:
3+ years of Java, Python or Scala
3+ Kafka (Topics, Producer/Consumer, KStream, KTable, KSQL)
3+ AWS Kinesis (streams, firehose and data analytics)
7 years of hands-on experience with data streaming systems and 10 or more years of data engineering

Additional Qualifications:
Demonstrated expertise with streaming data
Deep level understanding of Kafka
Assume ownership and ability to lead simultaneous projects
Strong time-management, prioritization, and organizational skills
Problem-solving and investigation skills
Strong interpersonal skills, with the ability to cultivate relationships and negotiate with internal clients
Ability to meet deadlines and partner timelines
Strong written and oral communication skills
Bachelor's Degree or Equivalent
SQL and familiarity with modern cloud databases like Snowflake
Frameworks: Spring Framework, Flink, JUnit, Mockito, Apache Flink.
Cloud Technologies: AWS (VPC, Kubernetes, EC2, Lambda, CloudWatch, etc)
Deployment Tools: Jenkins, Docker, Helm, Terraform
Monitoring tools: Grafana, Prometheus
CI/CD tools
Strong analytical and troubleshooting skills
Effective and clear communication of open project risks and team dependencies

ViacomCBS is an equal opportunity employer (EOE) including disability/vet.

At ViacomCBS, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. ViacomCBS is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.

If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access. https://www.viacomcbs.com/careers as a result of your disability. You can request reasonable accommodations by calling 212.846.5500 or by sending an email to viacomaccommodations@viacom.com. Only messages left for this purpose will be returned.

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